Constructing cluster of simple FPGA boards for cryptologic computations

In this paper, we propose an FPGA cluster infrastructure, which can be utilized in implementing cryptanalytic attacks and accelerating cryptographic operations. The cluster can be formed using simple and inexpensive, off-the-shelf FPGA boards featuring an FPGA device, local storage, CPLD, and network connection. Forming the cluster is simple and no effort for the hardware development is needed except for the hardware design for the actual computation. Using a softcore processor on FPGA, we are able to configure FPGA devices dynamically and change their configuration on the fly from a remote computer. The softcore on FPGA can execute relatively complicated programs for mundane tasks unworthy of FPGA resources. Finally, we propose and implement a fast and efficient dynamic configuration switch technique that is shown to be useful especially in cryptanalytic applications. Our infrastructure provides a cost-effective alternative for formerly proposed cryptanalytic engines based on FPGA devices

Quantifying Shannon's Work Function for Cryptanalytic Attacks

Attacks on cryptographic systems are limited by the available computational resources. A theoretical understanding of these resource limitations is needed to evaluate the security of cryptographic primitives and procedures. This study uses an Attacker versus Environment game formalism based on computability logic to quantify Shannon's work function and evaluate resource use in cryptanalysis. A simple cost function is defined which allows to quantify a wide range of theoretical and real computational resources. With this approach the use of custom hardware, e.g., FPGA boards, in cryptanalysis can be analyzed. Applied to real cryptanalytic problems, it raises, for instance, the expectation that the computer time needed to break some simple 90 bit strong cryptographic primitives might theoretically be less than two years.Comment: 19 page

A Review on Biological Inspired Computation in Cryptology

Cryptology is a field that concerned with cryptography and cryptanalysis. Cryptography, which is a key technology in providing a secure transmission of information, is a study of designing strong cryptographic algorithms, while cryptanalysis is a study of breaking the cipher. Recently biological approaches provide inspiration in solving problems from various fields. This paper reviews major works in the application of biological inspired computational (BIC) paradigm in cryptology. The paper focuses on three BIC approaches, namely, genetic algorithm (GA), artificial neural network (ANN) and artificial immune system (AIS). The findings show that the research on applications of biological approaches in cryptology is minimal as compared to other fields. To date only ANN and GA have been used in cryptanalysis and design of cryptographic primitives and protocols. Based on similarities that AIS has with ANN and GA, this paper provides insights for potential application of AIS in cryptology for further research

EVALUATION OF CRYPTOGRAPHIC ALGORITHMS

This article represents a synthesis of the evaluation methods for cryptographic algorithms and of their efficiency within practical applications. It approaches also the main operations carried out in cryptanalysis and the main categories and methods of attack in order to clarify the differences between evaluation concept and crypto algorithm cracking.cryptology, cryptanalysis, evaluation and cracking cryptographic algorithms

On The Cost of ASIC Hardware Crackers: A SHA-1 Case Study

International audienceIn February 2017, the SHA-1 hashing algorithm was practically broken using an identical-prefix collision attack implemented on a GPU cluster, and in January 2020 a chosen-prefix collision was first computed with practical implications on various security protocols. These advances opened the door for several research questions, such as the minimal cost to perform these attacks in practice. In particular, one may wonder what is the best technology for software/hardware cryptanalysis of such primitives. In this paper, we address some of these questions by studying the challenges and costs of building an ASIC cluster for performing attacks against a hash function. Our study takes into account different scenarios and includes two cryptanalytic strategies that can be used to find such collisions: a classical generic birthday search, and a state-of-the-art differential attack using neutral bits for SHA-1. We show that for generic attacks, GPU and ASIC poses a serious practical threat to primitives with security level ∼ 64 bits, with rented GPU a good solution for a one-off attack, and ASICs more efficient if the attack has to be run a few times. ASICs also pose a non-negligible security risk for primitives with 80-bit security. For differential attacks, GPUs (purchased or rented) are often a very cost-effective choice, but ASIC provides an alternative for organizations that can afford the initial cost and look for a compact, energy-efficient, reusable solution. In the case of SHA-1, we show that an ASIC cluster costing a few millions would be able to generate chosen-prefix collisions in a day or even in a minute. This extends the attack surface to TLS and SSH, for which the chosen-prefix collision would need to be generated very quickly

LEE: Light‐Weight Energy‐Efficient encryption algorithm for sensor networks

Data confidentiality in wireless sensor networks is mainly achieved by RC5 and Skipjack encryption algorithms. However, both algorithms have their weaknesses, for example RC5 supports variable-bit rotations, which are computationally expensive operations and Skipjack uses a key length of 80-bits, which is subject to brute force attack. In this paper we introduce a light-weight energy- fficient encryption-algorithm (LEE) for tiny embedded devices, such as sensor network nodes. We present experimental results of LEE under real sensor nodes operating in TinyOS. We also discuss the secrecy of our algorithm by presenting a security analysis of various tests and cryptanalytic attacks